一种修改的非单调线搜索SQP算法

提出了一种解非线性规划问题的修改的非单调线搜索算法,并给出了它的全局收敛性证明.不需要用罚函数作为价值函数,也不用滤子和可行性恢复阶段.该算法是基于多目标优化的思想一个迭代点被接受当且仅当目标函数值或是约束违反度函数值有充分的下降.数值结果与LANCELOT作了比较,表明该算法是可靠的.

An SQP Method with a Revised Non--Monotone Line Search

In the paper introduces a kind of revised non--monotone line search SQP method for constrained NLP problems is introduced, and the global convergence of this method is proved without using a penalty function as a merit function, a filter or the feasibility restoration phase. This method is based on the concept of multi--objective optimization: a trial point can be accepted if and only if either object function value decreases or the measure of violation constraints decreases. Numerical results, compared with LANCELOT, show that the approach is effective.